A few "Sell Work, Not Software" updated thoughts

[I feel ridiculous for the delay in this post. I wrote 90% of it months ago, but with the Oct 7th attacks and everything that resulted, the 10% lingered. I don’t write that as a political statement, more an emotional one. It takes mental space for me to write, and last quarter, I just didn’t have a lot of it. But back at it.]

I am grateful for all the conversations I've had with founders tackling "sell work, not software" opportunities.

Some follow-up reflections from those conversations. As always, if you are working on something in this space, I'd love to hear from you (sarah at benchmark dot com).

Reminder: Selling work opens up markets that weren't attractive for software businesses

One of the core hypotheses behind "selling work, not software" is that when you sell a 95% productivity improvement (vs squishier productivity improvement you sell against with software), you are able to charge *substantially* more for your service than you would have otherwise been able to if you sold software on a per seat basis. This can mean that the same end markets could be 10-50x larger than your software-model intuition would tell you. As I mentioned in my previous post, I’d guess a good test of the viability of a market opportunity to sell AI-built “work” is, crudely, whether there already exists a focused, outsourced group internationally to support it. 

It’s not about selling "virtual employees". It's about unbundling the specific tasks or outcomes that employees have traditionally performed, and selling those.

I've seen a bunch of companies that talk about selling "virtual employees". My gut is this is a limiting mental model. First, the reality is that LLM technology, while seemingly magic, is still early. It still performs best when given a limited scope vs the more general variety of tasks an "employee" typically handles. Second, how do you measure and compare the best employees? It's squishy. I prefer to think about what the skills or “jobs to be done" are, and what is the success metrics for each job. As you scale, you add more "jobs to be done" modules, which gives you more advantages with scale. This may eventually bundle back up into a reconstituted "employee", but by the winner, not the entrants.

It's ok to have a human in the loop - having it be *your* human in the loop (vs the customer's) creates clarity around the selling work model.

The reality is that LLMs are still early, and especially in cases where preciseness is important (e.g., legal use cases), and that preciseness requires a human in the loop to extend the surface area of what's possible. I think embrace this. But when embracing this looks like having a customer’s employees in the loop, it pulls you back into a world of selling software. On the other hand, if it is your own employees or contractors that are in the loop, you not only maintain more clarity on your business model of “selling work”, you also can ensure that those humans don’t just perform QA but also act as power users to give explicit feedback into your system to help it get better faster. Your job is to make progress towards automating them away.

Do these look like VC or PE opportunities?

I believe there will be both. The companies that align with the VC model are going to be ones that have the potential to escape competition -- to be dominant in their market. I've written about this here. My hypothesis is that the winner in a market is going to be able to keep on adding more "jobs to be done" automations, so eventually they are able to have the largest breadth of automations vs any competitor, giving them the economies of scale classic to software and the potential to escape competition. But as I said recently to one founder, to do this, you need to run like the wind. This is a skills land grab and there is going to be a lot of competition in the most obvious categories.

An "earned secret" even more important for selling work. Hard to see the opportunity if you aren't from the vertical.

I'd guess that the founding teams going after "work" are going to look different than cliche "college drop-out" profile. They are going to be teams that have lived and breathed a problem in a vertical, and see the wedge in the form of the first task to go after.